83-lambda-architecture.md

slug	id	title	date	comments	tags	description	references
83-lambda-architecture	83-lambda-architecture	Lambda Architecture	2018-10-23 10:30	true	system design	Lambda architecture = CQRS (batch layer + serving layer) + speed layer. It solves accuracy, latency, throughput problems of big data.	https://www.amazon.com/Big-Data-Principles-practices-scalable/dp/1617290343 https://mapr.com/resources/stream-processing-mapr/

Why lambda architecture?

To solve three problems introduced by big data

1. Accuracy (好)
2. Latency (快)
3. Throughput (多)

e.g. problems with scaling a pageview service in a traditional way

1. You start with a traditional relational database.
2. Then adding a pub-sub queue.
3. Then scaling by horizontal partitioning or sharding
4. Fault-tolerance issues begin
5. Data corruption happens

The key point is that ==X-axis dimension alone of the AKF scale cube is not good enough. We should introduce Y-axis / functional decomposition as well. Lambda architecture tells us how to do it for a data system.==

What is lambda architecture?

If we define a data system as

Query = function(all data)

Then a lambda architecture is

batch view = function(all data at the batching job's execution time)
realtime view = function(realtime view, new data)

query = function(batch view. realtime view)

==Lambda architecture = CQRS (batch layer + serving layer) + speed layer==